Robots & Robotics Series - Part 3 Testing

Robots & Robotics Series - Part 3 Testing verifies complete robotic systems and their key subsystems: industrial manipulators, mobile platforms, collaborative robots, and service robots. It covers motion mechanisms, drive units, end effectors, and sensor arrays. Testing confirms that a robot performs its specified functions with repeatable accuracy, behaves safely around operators, and withstands the electromagnetic environment of its installation.

Principle & mechanism

Robot testing compares measured behavior against specified behavior under controlled, repeatable conditions. Motion verification is grounded in kinematics. A robot command defines a target pose in joint or Cartesian space. Measurement instruments record the achieved pose. Position error, path deviation, and repeatability are derived from these records. Force and torque mechanisms are evaluated by loading the end effector against a reference transducer while recording command-versus-response relationships. Perception subsystems are verified by presenting known stimuli — target plates, calibrated distances, defined light levels — and comparing sensor output with reference values. Safety functions use a different mechanism. The tester triggers a hazardous condition, such as an approach into a protected zone, and records whether the protective stop completes within the specified time and distance. Across all modules, the common principle is traceability. Every measured quantity is referenced to an instrument whose accuracy is itself calibrated against a recognized standard.

Test objects and sample preparation

Test objects range from complete robot systems to subsystem samples such as joint modules, reducer assemblies, servo drives, grippers, vision cameras, and LiDAR units. Preparation begins with a documented configuration check. Firmware version, payload, end-effector mass, mounting orientation, and cable routing must match the test specification, because any deviation alters thermal and dynamic behavior. The sample is then stabilized in the laboratory environment, typically long enough to reach thermal equilibrium, since temperature drift affects encoder and structural dimensions. Mechanical preparation includes anchoring the robot base to a rigid fixture or measurement platform. A measurement coordinate frame is defined and referenced to a fixed datum. For subsystem samples, interfaces are reproduced with representative harnesses and loads rather than bare-bench connections. BefOre testing, a functional checkout confirms that all axes move, brakes release, and safety circuits respond. Any faults observed at this stage are recorded and cleared before formal measurement. The as-received condition is photographed and logged in the test record.

Core

test methods — motion performance & sensor calibration
Motion performance is commonly assessed with a laser tracker, which measures a reflector mounted at a defined tool point. Alternative instruments include ballbars for circular interpolation checks and camera-based motion capture for smaller workspaces. Typical runs include pose repeatability at multiple points distributed over the workspace, pose accuracy against commanded targets, and path accuracy along straight and circular trajectories at several speeds. Overshoot and settling time are measured on step commands. Velocity and acceleration profiles are recorded at low, nominal, and maximum speed settings. Drift is evaluated by repeating an identical cycle after a defined warm-up interval. Sensor calibration follows a separate track. Force-torque sensors are loaded against a reference dynamometer at points spanning the rated range. Encoders are compared with a reference angular instrument. Vision systems are verified with calibrated target plates under defined illumination. Distance sensors such as LiDAR are checked against reference positions on a linear rail or surveyed points. Each calibration yields an error table, and linear or polynomial fits are applied where the specification permits compensation.

Safety and EMC testing

Safety verification addresses both functional safety and electrical safety. Functional tests exercise protective stops, speed and separation monitoring, hand-guiding limits for collaborative operation, and force-limiting behavior during simulated contact. Impact is measured with instrumented tests on a calibrated force plate or biofidelic load device. Stop-time and stop-distance measurements establish the safety distance calculations required for safeguarded installations. Electrical safety covers protective bonding continuity, insulation resistance, dielectric withstand, and residual voltage checks after disconnection. EMC testing treats the robot both as a victim and a source. Radiated and conducted immunity tests subject the running robot to defined field strengths and transient phenomena while monitoring for faults, resets, or unintended motion. Emission tests measure radiated and conducted disturbances against the applicable limit lines. Because robots are large and dynamic, EMC tests may require special arrangements. These include extended cables, rotated antenna positions, or testing in standby, idle, and active operating modes to capture worst-case disturbance levels.

Performance

metrics and acceptance criteria
The core metrics are pose repeatability, pose accuracy, path accuracy, path repeatability, settling time, drift, payload capacity under specified deflection limits, and speed stability. Orientation error is expressed separately from position error where relevant. Safety metrics include stop time, stop distance, maximum contact force or pressure at defined contact locations, and the reaction time of protective functions. EMC results are judged as pass or fail against limit curves. Fault behavior during immunity testing is classified per the specified performance criterion. Acceptance criteria come from the product standard, the datasheet, or the agreed test specification. A typical structure defines nominal conditions, extended conditions, and the tolerances allowed at each. Results are reported with measurement uncertainty so that values near a limit can be judged correctly. A measurement is only accepted when the instrument uncertainty, environmental conditions, and test configuration are all within the stated ranges. Otherwise the result is documented as conditional, and the deviation is recorded in the report.

Application scenarios and test reports

Testing supports several scenarios across the robot life cycle. Type evaluation of a new model establishes baseline performance data before market release. Incoming or periodic verification of installed robots, often performed on-site with portable laser trackers or ballbars, detects degradation in repeatability that signals gearbox wear or mounting loosening. Collaborative robot assessments combine force-limiting measurements with functional safety verification for risk-reduced deployment alongside operators. Mobile platform programs add obstacle detection range, braking distance, and navigation repeatability to the standard motion suite. The test report should present, for each test item, the applied method and instrument, configuration and environmental conditions, raw results in tables or deviation plots, calculated metrics with uncertainty, and a clear pass or fail statement against each acceptance criterion. Deviations, incidents, and any retests are recorded transparently. A well-structured report allows the reader to reproduce the test and to compare results across units, sites, or design revisions. This is the practical output of the entire program.